Multivariate models are the basis by which on-line infrared analyzers are used to estimate component concentrations such as benzene content, saturates content, aromatics content and olefin content for motor gasolines, diesel fuels, jet fuels and process streams, and properties such as research and motor octane number of gasolines and cetane number for diesel fuels from infrared spectra. For example, Maggard describes the use of multivariate models for measuring paraffin, isoparaffin, aromatics, naphthene and olefin contents of motor gasolines and gasoline components (U.S. Pat. No. 5,349,189). Maggard also describes the use of MLR for measuring octane and cetane numbers (U.S. Pat. Nos. 4,963,745 and 5,349,188). Perry and Brown (U.S. Pat. No. 5,817,517) describe the use of FT-IR for determining the composition of feeds to hydrocarbon conversion, separation and blending processes.
The use of multivariate models is not limited to infrared analyzers. Jaffe describes the use of gas chromatography to estimate octane numbers for gasolines (U.S. Pat. No. 4,251,870). Ashe, Roussis, Fedora, Felsky and Fitzgerald describe the use of gas chromatography/mass spectrometry (GC/MS) and multivariate modeling for predicting chemical or physical properties of crude oils (U.S. Pat. No. 5,699,269). Cooper, Bledsoe, Wise, Sumner and Welch describe the use of Raman spectroscopy and multivariate modeling to estimate octane numbers and Reid vapor pressures of gasolines (U.S. Pat. No. 5,892,228).
Conventional asphalt binder specifications address binder properties such as penetration, viscosity, ductility, softening point, etc. which have a history of empirical correlation with asphalt pavement performance in service. The failure of specifications based on conventional properties to provide stable and durable road surfaces has resulted in the development of SUPERPAVE(trademark) specifications for rheologically-simple asphalt binders, based on rheological performance under limited frequency and temperature conditions. The SUPERPAVE(trademark) specifications do not currently deal with rheologically-complex materials and do not currently differentiate performance of asphalts in the same performance grade (PG).
Attempts to rank molecular components and identify an xe2x80x9cidealxe2x80x9d asphalt composition based on conventional and SUPERPAVE(trademark) performance parameters have not been successful. The relationship between composition and performance is masked by the use of a single performance parameter to rank the performance of each asphalt or vacuum residuum. The assigned ranking varies widely depending on which parameter is chosen (i.e., pen@25, SUPERPAVE spread between PG temperatures Tmax and T min, G* @Tg, etc.). The assigned ranking is also found to be too sensitive to the distillation cut temperature of the residuum.
It would be beneficial to find a method to rank and identify acceptable or ideal asphalt compositions by testing the feedstock or blends under consideration prior to asphalt production.
The present invention uses a combination of conventional and rheological parameters to develop a composite rheological ranking which accurately predicts the relative field performance of the asphalts and that rheologically-similar asphalts and vacuum residua exhibit commonalties in molecular composition, preferably measured by high resolution mass spectrometry. The abundance of specific molecular structures is indicative of superior asphalt pavement performance.